3.6%
Annual global electricity demand growth, 2026–2030
945 TWh
Projected data-centre electricity demand by 2030
~50%
Share of US electricity-demand growth to 2030 driven by data centres
175GW
Transmission capacity AI could help unlock
AI That Works in Operations
Energy operators already have years of SCADA, maintenance, inspection and asset data. The opportunity is not another dashboard. It is connecting that data to AI systems that help planners, engineers and field teams act sooner and with greater confidence.
Critical Questions for AI in Energy Leaders
These are the challenges we hear most from leaders looking to integrate ai in energy to optimize distributed infrastructure.
"How can I optimize asset performance across distributed infrastructure?"
"My compliance reporting is manual and time-consuming. Can AI help?"
"How do I implement predictive maintenance for critical equipment?"
Market Context
The energy challenge is becoming a coordination challenge
Electricity demand is accelerating just as power systems absorb new renewables, storage, electrified industry and AI-intensive data centres. Global electricity consumption is forecast to grow 3.6% annually through 2030, while grid infrastructure, connection capacity and operational flexibility are becoming binding constraints in major markets.
AI therefore sits on both sides of the equation. It is contributing to new electricity demand, but it can also help energy operators forecast load, plan capacity, optimize distributed assets, detect failures and make better use of existing infrastructure.
The opportunity is not simply to “add AI.” It is to connect intelligence safely to the systems, workflows and decisions that already operate the energy business.
3.5%+
Annual power demand growth to 2030
Global electricity demand is set to grow by more than 3.5% per year on average through the rest of this decade
945 TWh
Data centre electricity by 2030
Data centre consumption will more than double from 415 TWh in 2024, more than Japan’s total electricity use today
IEA, Energy and AI Report
$2.3T
Energy transition investment in 2025
Record global investment in clean energy technologies, up 8% from 2024, with renewables and batteries leading
BloombergNEF, 2026
2%
Of energy startup equity goes to AI
Despite AI’s transformative potential, only 2% of equity raised by energy startups has gone to AI-related companies
IEA, Energy and AI Report
The Opportunity
The energy transition demands intelligence
$2.3T
Record energy transition investment
MarketsandMarkets
$161B
Smart grid market by 2029
IEA, Energy and AI
175GW
Transmission capacity unlockable via AI
IEA, Energy and AI
300TWh
Potential AI-led electricity savings in buildings
What’s changing in our priority markets
Planning for a new load era
Data centres are becoming a major driver of electricity-demand growth. DOE is now applying foundation models to grid planning, targeting scenario analysis orders of magnitude faster than traditional methods.
Connection capacity becomes strategic
RTE had reserved nearly 18 GW for roughly 80 data-centre projects by May 2026 and is introducing ready-to-connect zones and accelerated connection models. Flexibility is increasingly part of the conversation, not merely new generation.
Reliability, efficiency and security converge
Japan expects electricity demand to rise as DX, AI and semiconductor investment expand, while METI is simultaneously addressing grid expansion, data-centre efficiency and AI-related cybersecurity risks for critical infrastructure.
Flexibility becomes infrastructure
Peak electricity demand is projected to rise 2.4–4.8% annually over the next decade. EMA is developing demand-side flexibility, grid digital twins and stronger energy-data governance alongside additional generation capacity.
our approach
We advise. We build. We Manage.
AI in energy companies face a familiar tension: strategy consultants deliver impressive transition roadmaps that stall at implementation, while technology vendors build systems that don’t account for regulatory complexity, grid physics, or market dynamics.
Redex brings both capabilities under one roof. We understand your operational realities (grid constraints, regulatory requirements, market structures) and we stay through implementation. We’re tech-agnostic, which means we recommend what works for your infrastructure, not what earns us a vendor commission.
Uptime Improvement
Maintenance Cost Reduction
Forecast Accuracy
How We Help
Capabilities built for AI in energy
We build for the realities of grid operations, regulatory compliance, and 24/7 reliability requirements.
AI Strategy & 60-Day Proof
Prioritize one operational problem by business value, data readiness and implementation risk. Move from baseline to working proof with measurable success criteria.
Operational Data & AI Integration
Connect SCADA, AMI, IoT, CMMS/EAM, ERP and enterprise data into the intelligence layer required for trustworthy AI.
Predictive Assets & Intelligent Inspection
Combine condition data, maintenance history, computer vision and anomaly detection to prioritize interventions before failures become outages.
Grid Planning, Forecasting & Flexibility
Apply AI to demand forecasting, renewable generation, capacity scenarios, storage dispatch and flexible loads so operators can make better use of constrained infrastructure.
Field & Engineering Copilots
Give engineers and technicians governed access to manuals, procedures, incident history and asset knowledge while keeping humans responsible for operational decisions.
AI Governance & Critical-Infrastructure Security
Design human-in-the-loop controls, auditability, access governance and secure integration patterns appropriate for safety-critical and regulated environments.
Energy Use Cases
Where AI creates value in energy
AI is already being deployed by energy companies to transform and optimize energy supply, electricity generation and transmission, and energy consumption. We help you capture these gains across four key dimensions.
Manufacturing Intelligence
Grid Reliability
From reactive maintenance to AI-driven asset strategy
AI-based fault detection rapidly identifies and pinpoints grid faults, reducing outage durations. Remote sensors and AI management can increase transmission capacity without building new lines.
Expected result:
30–50% reduction in outage duration
Manufacturing Intelligence
Operational Efficiency
End-to-end AI planning from demand to production
Widespread adoption of AI applications to optimize processes in energy operations can lead to significant energy savings, reducing waste and improving throughput across the value chain.
Insights:
Energy savings greater than Mexico's total consumption
Manufacturing Intelligence
Renewable Optimization
Simulate before you operate with AI-powered decision environments
AI improves forecasting and integration of variable renewable generation, reducing curtailment and emissions. Precision scheduling of battery storage maximizes clean energy dispatch.
Insights:
175 GW transmission capacity unlockable via AI
Manufacturing Intelligence
Workforce Productivity
Shift from “automation” → “augmentation”
Gen AI copilots trained on manuals and incident logs guide technicians in real time, boosting first-time fix rates. Edge-enabled drones and sensors shorten inspection cycles.
Insights
40% of utility control rooms using AI by 2027
client impact
What We Think & Do
For Every Scale
Enterprise-grade AI without the enterprise transformation programme
Mid-size utilities, IPPs and energy service companies often have valuable operational data but limited capacity for multi-year AI programmes. RedEx starts with one measurable workflow, uses the systems and data you already have, and takes it through a 60-day proof before deciding whether to scale.
01
Start small
Unlock value from existing SCADA, AMI, and operational data before investing in new infrastructure.
02
Prove value fast
4–8 week pilots with clear success metrics. No multi-year transformation programs.
03
Scale what works
Expand only after you see measurable results in reliability, efficiency, or cost reduction.
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